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Cooling demand model

Not all buildings in a TESSA study have cooling demand — many Swiss residential buildings historically did not have mechanical cooling. Cooling demand is calculated separately from heating demand and uses different modelling approaches for the residential and service sectors.

Swiss cooling demand model

Service-sector buildings

For service-sector buildings (offices, retail, hotels, hospitals, etc.), TESSA uses cooling demand projections derived statistically from existing cooling systems' properties and energy use data. This approach is based on the work of Li, X. et al. (see References), which developed Monte Carlo models of space cooling demand for Swiss service buildings under climate change.

The model outputs annual cooling energy (kWh) and peak cooling power (kW) per building archetype, calibrated against measured data from existing cooling installations.

Residential buildings

For residential buildings, present-day cooling demand is typically low or absent in Switzerland. TESSA estimates future cooling demand for residential buildings using EnergyPlus building energy simulation applied to archetypes from the open-access PACE dataset. These simulations cover a range of construction periods, building types, and climate scenarios.

The model provides:

  • Annual cooling energy demand (kWh/m² ERA)
  • Peak cooling power (kW per building)
  • Hourly load curves (8760 h)

Cooling demand for residential buildings is particularly relevant under future climate projections — buildings that have no mechanical cooling today are likely to require it by 2040–2050 under high-emission SSP scenarios.

How cooling demand is used in the network model

Cooling demand feeds into the network model the same way as heating demand:

  • It is summed across connected buildings at each building substation.
  • The network's aggregate cooling demand curve (p_c_kw, 8760 h) is used by the simulator.
  • For heating-and-cooling combined networks, cooling demand is subtracted from the net network load: heat recovered from cooling buildings reduces the energy the heat sources must supply.

Origin tracking

The cooling demand origin field qc_origin records how each building's cooling demand was determined (archetype model, user-supplied value, or not set). See Data quality and confidence.

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